Sustainable Energy Technologies and Assessments最新文献

{"title":"Fabrication and performance evaluation of the NPC/amorphous-Sn2P2O7 by dealloying of CuNiSnP alloy for supercapacitor application","authors":"Mircea Nicolaescu ,&nbsp;Mina-Ionela Popescu (m Morariu) ,&nbsp;Cosmin Codrean ,&nbsp;Iosif Hulka ,&nbsp;Corina Orha ,&nbsp;Carmen Lazau ,&nbsp;Cornelia Bandas ,&nbsp;Narcis Duteanu","doi":"10.1016/j.seta.2025.104383","DOIUrl":"10.1016/j.seta.2025.104383","url":null,"abstract":"<div><div>Present study focuses on the evaluation of the energy storage performance of possible pyrophosphate supercapacitor materials obtained by dealloying process. The electrochemical behavior was investigated by cyclic voltammetry (CV), galvanostatic charge–discharge (GCD) and electrochemical impedance spectroscopy (EIS) techniques using a system based on three-electrode cell in 1 M KOH electrolyte solution. A direct assessment of the influence of dealloying time for capacitance was performed, showing that partial dealloying improves energy storage. Furthermore, the synthesized materials were investigated morpho-structurally to present behavior of the materials at immersion times between 3 and 24 h. Obtained results presents that the highest capacitance value about 269.36 mF cm⁻² measured from CV analysis was observed for the electrode at 3 h immersion time at 5 mV s⁻¹ scan rate. The GCD results confirmed also the superiority of the electrode material by recording the maximum specific capacitance of 268.7 mF cm⁻² at 1 mA cm⁻² calculated for the electrode at 3 h immersion time. All the as-synthesized electrodes presented an excellent cyclic stability showing an increase in retention rates over 100 %. For the as-obtained electrode a retention rate about 129.33 % at 24 h immersion time over 500 cycles, was obtained. In addition, aqueous symmetric supercapacitors were assembled based on the experimental program. Capacitance values were calculated from the CV data as a function of potential window and scan rate. The highest capacitance was observed for the CSP-12 h//CSP-12 h symmetric supercapacitor, reaching 49.24 mF cm⁻² at 1.4 V. As a function of scan rate, the CSP-24 h//CSP-24 h device exhibited the highest capacitance, reaching 45.72 mF cm⁻² at 5 mV s⁻¹. GCD measurements as a function of potential window showed that the CSP-6 h//CSP-6 h and CSP-12 h//CSP-12 h devices demonstrated the best performance, with the highest capacitance values of approximately 46 mF cm⁻² achieved at 1.4 V. Furthermore, the CSP-12 h//CSP-12 h device delivered a power density of 5.46 mW cm⁻² at an energy density of 0.027 mWh cm⁻². Over 3000 cycles, the maximum retention rate was approximately 30.42 %, observed for the CSP-3 h//CSP-3 h device. This research presents a promising technique for producing pyrophosphate material for supercapacitor application.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"80 ","pages":"Article 104383"},"PeriodicalIF":7.1,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maximizing efficiency with active diameter modulation of vertical axis wind turbine","authors":"Ken-Yeen Lee ,&nbsp;Andrew Cruden ,&nbsp;Jo-Han Ng ,&nbsp;Kok-Hoe Wong","doi":"10.1016/j.seta.2025.104363","DOIUrl":"10.1016/j.seta.2025.104363","url":null,"abstract":"<div><div>Wind turbines rely heavily on prevailing wind conditions, yet the dynamic nature of wind often limits the efficiency of turbines with fixed dimensions. While previous research has explored variable concepts such as pitch angle, deformable aerofoils, etc., studies on variable solidity are scarce. This study proposes a novel variable diameter vertical axis wind turbine (VD-VAWT) designed to dynamically adapt to varying tip speed ratios (TSR), enhancing performance and expanding its wind capture range. This VD-VAWT comprises a special mechanism design that enables the turbine blade to slide along the strut. Experiments were conducted on a VD-VAWT with two straight-bladed NACA0018 aerofoils. Initially, the fixed diameter experiments spanning 300 mm to 800 mm were conducted which identified 600 mm as the optimal diameter, achieving a maximum power coefficient (<em>C_P,</em> _max) of 0.2748. The active control VD-VAWT demonstrated significant performance improvements, with power yields surpassing fixed diameter turbines by 34 % at 600 mm and 68 % at 800 mm. While changing its diameter, it can maximize the <em>C_P</em> at different TSRs. In addition, the VD-VAWT enhanced self-starting capabilities, dynamic self-regulation for optimal conditions, and potential storm protection. This innovation demonstrates the potential of adaptable turbines to achieve higher efficiency and versatility in fluctuating wind conditions.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"80 ","pages":"Article 104363"},"PeriodicalIF":7.1,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144213202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kinetic modeling and optimization of biogas production from maize silage for sustainable energy systems","authors":"K. Bułkowska ,&nbsp;I. Białobrzewski ,&nbsp;T. Pokój","doi":"10.1016/j.seta.2025.104395","DOIUrl":"10.1016/j.seta.2025.104395","url":null,"abstract":"<div><div>Anaerobic digestion is a crucial process for sustainable energy production and offers a way to produce biogas from agricultural biomass such as maize silage. This study evaluates the application of a modified Anaerobic Digestion Model No. 1 (ADM1) to improve simulation accuracy for biogas production from maize silage digestion. Key modifications included the inclusion of lactic acid, <em>iso</em>-valeric acid and <em>iso</em>-butyric acid, essential intermediates of maize silage fermentation. A sensitivity analysis identified the disintegration constant (k_dis = 0.191 d⁻¹) and the hydrolysis rate constant for carbohydrates (k_{hyd_ch} = 1.624 d⁻¹) as critical parameters. Optimization of the parameters using genetic algorithms has improved the accuracy of the model, as shown by an improved Nash-Sutcliffe Efficiency coefficient. This research highlights the importance of precise parameter tuning to optimize biogas production and illustrates the potential of advanced modeling to support energy efficiency in agricultural biogas systems.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"80 ","pages":"Article 104395"},"PeriodicalIF":7.1,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unlocking Sweden’s hydrogen export potential: A Techno-Economic analysis of compressed hydrogen and chemical carriers","authors":"Kumail Marnate,&nbsp;Stefan Grönkvist","doi":"10.1016/j.seta.2025.104359","DOIUrl":"10.1016/j.seta.2025.104359","url":null,"abstract":"<div><div>Sweden, with its abundant access to low-cost, fossil-free electricity, is well-positioned to become a significant hydrogen exporter. This study presents a techno-economic analysis of different hydrogen carriers—compressed hydrogen, methanol, ammonia, and liquid organic hydrogen carriers (LOHC)—for export applications. Using the Northern Green Crane Project as a reference for scale, the analysis focuses on cost optimization for hydrogen production, storage, and transportation. A linear programming model is developed to optimize capacities and operational strategies for each carrier, ensuring a fair basis for comparison. Results indicate that LOHC and ammonia are competitive with compressed hydrogen, showing particular promise for larger-scale, long-distance deliveries. These findings offer valuable insights for policymakers and industry stakeholders developing Sweden’s hydrogen export strategies.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"80 ","pages":"Article 104359"},"PeriodicalIF":7.1,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144213201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on data-driven group consensus decision-making of green methanol vehicle evaluation based on BERTopic text mining","authors":"Qian Li ,&nbsp;Hong Chen ,&nbsp;Ruyin Long ,&nbsp;Zhiping Huang ,&nbsp;Shuhan Yang ,&nbsp;Qingqing Sun ,&nbsp;Yunhao Sun ,&nbsp;Xiangyang Ye","doi":"10.1016/j.seta.2025.104362","DOIUrl":"10.1016/j.seta.2025.104362","url":null,"abstract":"<div><div>In response to climate change and energy crises, a scenario has emerged globally where multiple technical routes coexist, including electric, hydrogen, and methanol vehicles. Green methanol vehicles (GMV), a new path for future travel, the reported media data is easy to influence decision-makers’ (DMs’) evaluation on them. For the issue of GMV evaluation, this study proposes a data-driven group consensus decision-making model based on text mining. Firstly, the topics of related methanol vehicle in news reports are extracted through BERTopic text mining model, which employs a pre-trained transformer-based language technology to determine criteria and weights. Then, to address the problem of inconsistent results obtained from different centrality calculation methods in social network, a method for determining the DMs’ weights based on multidimensional advantages of centrality theory and water-filling theory is proposed. Furthermore, to uncover the psychological black box of DMs, the K-means method and bounded confidence model are employed to design a dynamic large-scale group consensus mechanism, ensuring effective integration of decision-making information and consensus achievement. Finally, the proposed model is used to evaluate of GMV, coal-to-methanol, gasoline, and electric vehicles. Discussions on production-living-ecological benefits for GMV are used to confirm the practicality of the proposed model.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"80 ","pages":"Article 104362"},"PeriodicalIF":7.1,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconstructing the upwind field of wind turbines using LiDAR data","authors":"Mohammad Khezri ,&nbsp;Mohammad Javad Maghrebi ,&nbsp;Esmail Mahmoodi ,&nbsp;Uwe Ritschel","doi":"10.1016/j.seta.2025.104382","DOIUrl":"10.1016/j.seta.2025.104382","url":null,"abstract":"<div><div>With the growing demand for renewable energy, optimizing wind turbine performance requires accurate understanding of upstream wind flow. This study introduces a model for characterizing upwind flow using two years of raw radial wind speed (RWS) data from a fixed 4-beam nacelle-mounted LiDAR system. The model incorporates axial and lateral wind speed components, wind shear exponent (WSE), veer, and wind turbine induction factor. These parameters are optimized by minimizing the mean absolute error (MAE) using stochastic gradient descent and the Adam optimization algorithm. Hypothesis testing for linear veer profiles, power law shear, and induction zone models demonstrated statistical significance at the 95 % confidence level in 99 %, 90 %, and 92 % of cases, respectively. The model achieved an MAE of 0.08 m/s (1.3 %) for reconstructing horizontal RWS. Notable diurnal variations were observed in model parameters; at night, when the atmospheric boundary layer (ABL) is stable, WSE, veer, and axial wind speed components increase, while during the day, ABL instability leads to higher turbulence intensity. The model’s short optimization duration (0.25 s) makes it suitable for real-time applications in wind turbine control, such as alignment and yaw control for wake steering strategies using nacelle-mounted LiDAR.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"80 ","pages":"Article 104382"},"PeriodicalIF":7.1,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy flow illustration and exergy efficiency analysis of a novel household energy management system employing hybrid sustainable resources and adaptive co-storage of cold, heat and electricity","authors":"Yan-Ao-Ming Xi ,&nbsp;Yun-Ze Li ,&nbsp;Hai-Hao Jiang","doi":"10.1016/j.seta.2025.104370","DOIUrl":"10.1016/j.seta.2025.104370","url":null,"abstract":"<div><div>Households are an important part of social energy consumption. To reduce household energy consumption and CO₂ emissions while promoting sustainable development, a novel household energy management system employing hybrid sustainable resources and adaptive co-storage of cold, heat and electricity (AHHES) is proposed. The system makes full use of the local solar and wind resources and improves flexibility and adaptivity through the co-storage of cold, heat and electricity. Energy flow and exergy efficiency analysis model is established and simulation calculations under different seasons and weathers are performed to evaluate the thermodynamic performance of the system. Simulation results show high low-carbon energy utilization and low energy loss of designed system. The share of renewable energy sources in total energy supply is above 50% in summer and above 30% in winter. Except for the PV-solar thermal hybrid module, the energy flow loss of all other modules is at a low level. The exergy efficiency of hot storage tank (HST), cold storage tank (CST), and pre-heat exchanger (PHE) is significantly higher than that of conventional refrigeration or heating equipment such as water chillers (WC), air-conditioning refrigeration cycle (RC), or heat pump (HP), demonstrating that the AHHES exhibits superior energy-saving potential.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"80 ","pages":"Article 104370"},"PeriodicalIF":7.1,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient scheduling of electric vehicle resources in wind-integrated distribution networks","authors":"Pragya Singh Savita ,&nbsp;Soumyabrata Das ,&nbsp;Padmanabh Thakur ,&nbsp;Asheesh K. Singh","doi":"10.1016/j.seta.2025.104385","DOIUrl":"10.1016/j.seta.2025.104385","url":null,"abstract":"<div><div>The increasing integration of Electric Vehicles (EVs) into power grids poses challenges in load management and grid stability, especially in renewable energy sources (RES)-integrated distribution systems. This study optimizes load management in such systems using a priority-based scheduling strategy for Vehicle-to-Grid and Grid-to-Vehicle operations. A penalty factor-based objective function minimizes load variance, addressing EV charging and renewable power uncertainties via Monte Carlo Simulation and the Weibull distribution function. The Opposition-based Competitive Swarm Optimizer (OCSO) is employed for optimization and benchmarked against Competitive Swarm Optimizer and Particle Swarm Optimizer. Results show OCSO achieves up to 31.72% load variance reduction, enhancing voltage stability. The proposed method, implemented in MATLAB 2023®, is validated on IEEE 33-bus and IEEE 69-bus systems, demonstrating effectiveness in integrating EVs and RESs.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"80 ","pages":"Article 104385"},"PeriodicalIF":7.1,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A foresight study of carbon emission control in energy supply: A case of Mexico","authors":"Mostafa Ahadian ,&nbsp;Mostafa Hajiaghaei-Keshteli ,&nbsp;Benyamin Chahkandi ,&nbsp;Fatemeh Gholian-Jouybari ,&nbsp;Neale R. Smith ,&nbsp;Stanisław Wacławek ,&nbsp;Mohammad Gheibi","doi":"10.1016/j.seta.2025.104343","DOIUrl":"10.1016/j.seta.2025.104343","url":null,"abstract":"<div><div>The purpose of this paper is to explore an integrated machine learning and expert-based strategic foresight methodology for guiding policies aimed at reducing carbon emissions. The approach is pursued to provide data-driven predictive analytics combined with structured policy road mapping. Gaussian Process machine learning models are developed to forecast carbon emissions accurately based on relevant parameters. A phased foresight framework, leveraging collective expert wisdom, is also developed to generate actionable short-, medium-, and long-term strategic plans. This work finds that the Gaussian Process models exhibited strong predictive accuracy with a 0.93 correlation, providing a means to quantify expected outcomes under proposed policy scenarios. Based on expertise, phased foresight roadmaps provide tangible strategies to guide practical implementation. Before broader socioeconomic incentives drive widespread adoption, short-term technical solutions establish the foundation. Also, innovation ecosystems ensure long-term progress for the carbon emission control in the case study. Integrated and evidence-based carbon policy informational tools as well as structured strategic plans, address the pressing need for actionable knowledge to support national and global decarbonization efforts. This methodology offers policymakers robust analytical capabilities for modeling options and scenario impacts, as well as tangible recommendations. Contributions address critical gaps preventing carbon reduction commitments from being realized.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"80 ","pages":"Article 104343"},"PeriodicalIF":7.1,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance analysis and environmental feasibility of agrivoltaics using diverse photovoltaic technologies","authors":"Utkarsh Shukla ,&nbsp;Prabhakar Tiwari ,&nbsp;Shekhar Yadav ,&nbsp;Sumit Tiwari","doi":"10.1016/j.seta.2025.104380","DOIUrl":"10.1016/j.seta.2025.104380","url":null,"abstract":"<div><div>The integration of agricultural and electrical outputs has spurred interest in the integration of land use for both food security and energy generation. To guarantee sustainability, the environmental effects of photovoltaic (PV) systems, such as carbon emissions and efficiency fluctuations, need to be carefully assessed. With an emphasis on their effects on land usage, plant growth, and energy output, this study sought to evaluate the performance of ground-mounted solar power plants (GmSPPs) in northwest India. It also aimed to assess how various PV technologies affected the environment. Three 1000 kWp, three 10 kWp, and three 2 kWp installations were among the six SPPs that were the subject of a land utilization study. Copper indium gallium selenide (CIS), polycrystalline silicon (poly-Si), and hydrogenated amorphous silicon (a-Si:H) PV modules were examined. The effects of temperature and humidity variations on plant development in alluvial soil were examined while the PV regions were shaded. The study found that CIS PV plants with smaller capacities generated more power than larger ones. Module efficiency ranged between 7 % and 17 %, with final yields of 4.07–4.47 kWh/kWp/day and performance ratios from 73.6 to 80.7 %. Shaded areas exhibited improved plant growth, likely due to microclimatic changes induced by PV modules.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"80 ","pages":"Article 104380"},"PeriodicalIF":7.1,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}